Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use halvion/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halvion/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="halvion/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("halvion/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("halvion/finetuning-sentiment-model-3000-samples") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d014c4cd305d20748eb81a19a6cae103d37150444452e450467712ca1fe5f59
- Size of remote file:
- 268 MB
- SHA256:
- c60f1ee68e32a39f1596dc416f0b147fd695909459756433e92e5534db83eaf0
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